David Winsemius
On Mar 18, 2009, at 1:54 PM, Aaron Spivak wrote:
> Hi,
> This is my first time posting to the mailing list, so if I'm doing
> something
> wrong, just let me know. I've taken ~1000 samples from 8 biological
> replicates, and I want to somehow combine the density functions of the
> replicates. Currently, I can plot the density function for each
> biological
> replicate, and I'd like to see how pool of replicates compares to a
> simulation I conducted earlier. I can compare each replicate to the
> simulation, but there's a fair amount of variability between
> replicates.
> I'd like to take the geometric mean of the density functions at each
> point
> along the x-axis, but when I compute:
>
>> a<-density(A[,1][A[,1]>=0], n=2^15)
>> b<-density(A[,3][A[,3]>=0], n=2^15)
>> a$x[1]
> [1] -70.47504
>> b$x[1]
> [1] -69.28902
>
> So I can't simply compute the mean across y-values, because the x-
> values
> don't match. Is there a way to set the x-values to be the same for
> multiple
> density plots? Also, there are no negative values in the dataset,
> so I'd
> like to bound the x-axis at 0 if at all possible? Is there a
> standard way
> to combine density functions? Thanks for the advice.
> -Aaron Spivak
>
> ps. I thought about just pooling all measurements, but I don't think
> that's
> appropriate because they are from different replicates and the
> smoothing
> kernel depends on the variance in the sample to calculate the
> distribution.
>
> [[alternative HTML version deleted]]
>
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David Winsemius, MD
Heritage Laboratories
West Hartford, CT